Analytics Engineer

Analytics Engineer - Consumer Data Science

On Reddit, people can dive into anything through experiences built around their interests, hobbies, and passions. Our mission is to empower communities and make their knowledge accessible to everyone. With over 100,000 active communities and over 120 million daily active users, it is home to the most open and authentic conversations on the internet. Reddit’s unique and differentiated product is extremely attractive to advertisers, who can reach out to and connect to our users authentically.

We are looking for a talented and driven individual to be a key part of our Analytics Engineering team within the Data Science organization, focused on the Consumer domain. We are looking for someone who can work closely with Data Scientists and members of Consumer cross-functional teams (Product, Engineering, and Design) to curate, develop, and deploy the right data and analytic tooling to drive Reddit’s product forward and provide a data and tooling foundation that will last decades. Your work will empower thousands of your colleagues to improve the user experience and grow our consumer base.

Successful candidates have a strong track record of understanding and deeply caring about the purpose of data to support business goals, and can act as an effective conduit between Data Producers and Data Consumers. This role sits at the intersection of Data Science and Data Engineering, and the ideal candidate has skills, experience, and passion in both areas.

Reddit has a flexible workforce! If you happen to live close to one of our physical office locations, our doors are open so you can come into the office as often as you'd like. Don't live near one of our offices? No worries: You can apply to work remotely in any country in which we have a physical presence.

Responsibilities

• Be an Analytics Engineering leader within the Consumer organization and a key contributor and collaborator to the success of Data Science data quality, performance, reliability, and automation initiatives.
• Be the data steward for Consumer products: architect and improve the collection of underlying data while also creating ETLs, reporting dashboards, data aggregations and other deliverables needed for product feature tracking, user retention analysis, A/B testing, and a large number of other data-driven activities.
• Develop and maintain robust data pipelines and workflows for data ingestion, processing, and transformation. Work closely with engineering to ensure the quality and reliability of these data pipelines.
• Create user-friendly tools and applications for internal use across Data Science and cross-functional teams, streamlining data analysis and reporting processes. Drive widespread adoption of these tools and applications with a relentless focus on usability and impact.